Labeling and authenticating using a microtag

ABSTRACT

A system for encoding energy peaks of an identifier comprises an encoder. The encoder is configured to define a readable spectral range of an identifier. The identifier comprises a rugate microtag. The encoder is configured to divide the readable spectral range into a plurality of bins. The encoder is configured to encode in a center of a bin near one end of the readable spectral range a reference peak. The encoder is configured to encode in a center of each of a set of bins a set of peaks of a data pattern within the readable spectral range.

CROSS REFERENCE TO OTHER APPLICATIONS

This application is a continuation of co-pending U.S. patent applicationSer. No. 12/966,901, entitled LABELING AND AUTHENTICATING USING AMICROTAG filed Dec. 13, 2010 which is incorporated herein by referencefor all purposes, which claims priority to U.S. Provisional ApplicationNo. 61/288,289, entitled METHOD AND SYSTEM FOR STORING AND RETRIEVINGINFORMATION USING RUGATE MICROTAGS filed Dec. 19, 2009 which isincorporated herein by reference for all purposes.

BACKGROUND OF THE INVENTION

Porous silicon microtags have the advantage of being able to labelproducts. The microtags have an additional advantage in that they aredifficult to reproduce and read without specialized equipment. However,to date, the tags have not been able to store sufficient information forsome labeling tasks due to complexities (e.g., sidelobes) in theoptically read spectrum.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of the invention are disclosed in the followingdetailed description and the accompanying drawings.

FIG. 1A is a SEM image illustrating an embodiment of a silicon film.

FIG. 1B is a SEM image illustrating an example of porous silicon columnsin one embodiment.

FIG. 2 are a block diagram illustrating an embodiment of a process forcreating a rugate microtag.

FIG. 3 is a block diagram illustrating an embodiment of basic systemconcepts from binary data input and encoding of a microtag to thereadout, decoding, and error correction of the information stored on amicrotag.

FIG. 4 are graphs illustrating a single and a composite reflectancespectrum read from an embodiment of microtags without any normalization.

FIG. 5A are graphs illustrating embodiments of normalized peak energies.

FIG. 5B is a flow diagram illustrating an embodiment of a process forencoding energy peaks of an identifier.

FIG. 5C is a flow diagram illustrating an embodiment of a process fordecoding energy peaks of an identifier.

FIG. 6 are graphs illustrating an embodiment of allowed rugate peakpositions.

FIG. 7 is a graph illustrating the squared error in measured peakposition summed for each peak in a spectrum in one embodiment.

FIG. 8 is a graph illustrating the squared magnitude of both thesurface-derived interference fringes r_(s) and a typical rugate peakr_(rug) in one embodiment.

FIG. 9 is a graph illustrating an embodiment of a calculated rugatefilter reflectance spectrum.

FIG. 10 is a graph illustrating an embodiment of a comparison of fullsurface-derived reflectance to a simple approximation.

FIG. 11 are graphs illustrating embodiments of four different etchingwaveforms of the same frequency and amplitude, but different phases.

FIG. 12 are graphs illustrating an embodiment of simulated reflectancespectra corresponding to the four current density waveforms along withfitted spectra.

FIG. 13 is a graph illustrating an embodiment of a relation betweensidelobe asymmetry and rugate phase.

FIG. 14 is a graph illustrating an embodiment two rugate index profiles.

FIG. 15 is a graph illustrating an embodiment of side lobe asymmetrycalculation for two rugate peaks differing only by phase.

DETAILED DESCRIPTION

The invention can be implemented in numerous ways, including as aprocess; an apparatus; a system; a composition of matter; a computerprogram product embodied on a computer readable storage medium; and/or aprocessor, such as a processor configured to execute instructions storedon and/or provided by a memory coupled to the processor. In thisspecification, these implementations, or any other form that theinvention may take, may be referred to as techniques. In general, theorder of the steps of disclosed processes may be altered within thescope of the invention. Unless stated otherwise, a component such as aprocessor or a memory described as being configured to perform a taskmay be implemented as a general component that is temporarily configuredto perform the task at a given time or a specific component that ismanufactured to perform the task. As used herein, the term ‘processor’refers to one or more devices, circuits, and/or processing coresconfigured to process data, such as computer program instructions.

A detailed description of one or more embodiments of the invention isprovided below along with accompanying figures that illustrate theprinciples of the invention. The invention is described in connectionwith such embodiments, but the invention is not limited to anyembodiment. The scope of the invention is limited only by the claims andthe invention encompasses numerous alternatives, modifications andequivalents. Numerous specific details are set forth in the followingdescription in order to provide a thorough understanding of theinvention. These details are provided for the purpose of example and theinvention may be practiced according to the claims without some or allof these specific details. For the purpose of clarity, technicalmaterial that is known in the technical fields related to the inventionhas not been described in detail so that the invention is notunnecessarily obscured.

A system for encoding energy peaks of an identifier comprises anencoder. The encoder is configured to define a readable spectral rangeof an identifier. The identifier comprises a rugate microtag. Theencoder is configured to divide the readable spectral range into aplurality of bins. The encoder is configured to encode in a center of abin near one end of the readable spectral range a reference peak. Theencoder is configured to encode in a center of each of a set of bins aset of peaks of a data pattern within the readable spectral range.

A system for decoding energy peaks of an identifier comprises a decoder.The decoder is configured to receive a reference peak associated with anidentifier. The identifier comprises a rugate microtag. The decoder isconfigured to receive a set of data pattern peak positions associatedwith the identifier. The decoder is configured to determine a farthestpeak of the set of data pattern peak positions from the reference peakposition. The decoder is configured to determine a set of data patternpeak bins from the set of data pattern peak positions. The set of datapattern peak bins are based at least in part on a lowest error for a setof potential data patter peak bins corresponding to the set of datapattern peak positions for a potential bin position for the farthestpeak.

A system for producing an identifier comprises a processor and anetcher. The processor is configured to determine an identifying datavalue. The etcher for producing an identifier. The identifier comprisesa rugate phase tag. The identifier is identified using the identifyingdata value. The rugate phase tag encodes the identifying data value atleast in part using a calculated rugate phase information. In someembodiments, the rugate phase tag comprises oxidized etched silicon.

A system for reading an identifier comprises a reader and a processor.The reader for reading an identifying data value of an identifier. Theidentifier comprises a rugate phase tag. The rugate phase tag encodesthe identifying data value at least in part using a calculated rugatephase information. The processor is configured to determine anidentifying data value.

Porous silicon films have been shown to exhibit spectral propertiesdependent on thickness, porosity, and pore diameter. The pores areproduced by means of an electrochemical etching wherein the etchingcurrent density determines the porosity, which is the volumetricfraction of the pores inside a layer of film, and in the case of rugatefilters, the etching current waveform determines spectral reflectancepeaks. The film's porosity relates directly to the material's opticalindex of refraction. More porosity leads to a lower refractive indexbecause the dielectric effective medium contains more air.

Spectral peaks, useful for encoding information, can be created andcontrolled through alternating layers of fixed or varying porosity, suchas a Bragg structure, through a single layer of continuously varyingporosity, as in a rugate filter, or through various combinationsthereof. A rugate is a gradient-index interference filter with asine-wave refractive index profile.

The spectral properties can be observed by analyzing reflected ortransmitted light either from, or through, these films, respectivelycalled “reflectance spectra” and “transmission spectra”. Using a lightsource of multiple wavelengths, spectroscopic analysis can revealspectral structure in both the reflected or transmitted light, whereinboth the wavelength and the amplitude or intensity of the spectral peakscontains encoded information. The encoded information can be useful formeans of labeling or authenticating various products or objects when thefilms, or pieces thereof, are attached to, or embedded within a product,object, or other item.

The films can be broken into small pieces, or tags, ranging fromhundreds of nanometers to hundreds of micrometers or more in size. Filmthicknesses can range from a few micrometers to hundreds of micrometersor more. Further, the integrity and strength of the spectral structurecan be enhanced by oxidizing these films, thus forming optically clearsilicon dioxide, also known as silica. A porous silica film, aka“optical film”, can be diced, or otherwise fragmented, to create“optical microtags”, or simply “tags”. In various embodiments, thesilicon film is fragmented, then oxidized into silica, oxidized and thenfragmented, or any other appropriate sequence of steps to produce arugate microtag. Porous silica microtags have been shown to exhibit thesame spectral properties of their parent film without losing any of theproperties or benefits of the parent. These spectral properties includefeatures, such as peaks, that are determined by the various porositiesof the film or film layers.

The following focuses on rugate filters of porous silicon, and poroussilica, interchangeably called herein “nanoporous optical filters”, or“nanoporous filters”, or preferably “rugate microtags” (singularly,“rugate microtag”), wherein each rugate spectral peak in the reflectancespectrum of a rugate microtag (each spectral peak that corresponds to asinusoidal oscillation along the depth of the microtag refractive indexis a “rugate peak”) can be attributed to a different sinusoidalcomponent of the electrochemical etching waveform. It will be obvious tothose skilled in the art that the following can be extended bymodification of the formulas herein to layered, Bragg-like film andmicrotag designs.

Silicon wafers are processed into thin, porous, silicon films with acontrollable density of embedded pores (“rugate films”). This processallows the control of the optical properties of silicon films, whichcarry over into the optical properties of the silica films obtainedthrough oxidation. Silica films produced using this technique can bemade into small tags (i.e., rugate microtags) that carry informationencoded in the form of their particular optical spectrum. In someembodiments, silicon is etched and then fragmented and then oxidized. Aparticular optical spectrum, whether reflective or transmissive, can becharacterized by distinguishable traits such as peak shape, number,position, or amplitude. The collection of unique traits for a particularspectrum constitutes its “state”. We use the term ‘state’ as used ininformation theory. In information theory, if the number of states wereto double, an additional bit would be necessary to uniquely label eachstate. Unlike a typical logic gate, which has only two voltage states(high and low), and thus is capable of storing at most one bit, traitsin rugate microtags, such as peak shape, number, position, or amplitude,can have more than two values, and each unique set of values of thedifferent traits constitutes a discrete state.

FIG. 1A is a SEM image illustrating an embodiment of a silicon film. Inthe example shown, the scanning electron microscope (SEM) image shows across section of a porous nanostructure of a porous silicon film. Porediameter in region 100 is larger than in region 102. Scale bar 104indicates a 1 m length scale for the SEM image. The pore size iscontrolled by the current applied during etching. In this sample, thecurrent was decreased suddenly during preparation, resulting in theabrupt decrease in pore diameter observed between region 100 and region102. The porous silicon film was made by acid-etching a silicon wafer inthe presence of an electric current. The etching process creates smallpores or cavities in the wafer, the dimensions of which are controlledby the current density of the etching current waveform. The dimensionsthat are controlled include the depth of pores etched in the siliconfilm and the diameter and density of the pores; size and densitymodulation is achieved by controlling electric current density withtime. Although the sizes of the pores vary, over a wide range of currentdensities, the pore size is much smaller than the wavelength of opticallight. As a result, the optical properties of the porous silicon, asmeasured by an incident optical photon, is akin to an average of thesilicon and air present within the porous silicon over a distancecomparable to the wavelength of the photon. By modulating the poredensity as a function of film depth, the index of refraction of a poroussilicon film is similarly modulated between that of pure silicon andair. After etching, the film is completely oxidized into silica,resulting in a thin film with a controlled index of refraction (n) as afunction of depth between that of silica (n˜1.5) and air (n=1). Thesefilms meet the requirements listed above for a means to encodeinformation in the optical reflectivity spectrum of a silica tag, i.e.,for a means to create a rugate microtag.

FIG. 1B is a SEM image illustrating an example of porous silicon columnsin one embodiment. In the example shown, porous silicon columns (e.g.,column 110 and column 112) are produced by lithographic patterning andetching. The image shows a 2-dimensional array of porous silicon columnsthat are approximately 25 microns in diameter and 10 microns in height.Scale bar 114 indicates a 50 m length scale for the SEM image. Thecolumns are lifted off the substrate with a current pulse to createrugate microtags.

FIG. 2 are a block diagram illustrating an embodiment of a process forcreating a rugate microtag. In the example shown, a waveformsuperposition method is used to design a spectral state. Four sine waveswith different frequencies (A—shows sine waves of four frequencies, f1,f2, f3, and f4, with equal amplitudes as a function of time) are addedtogether to generate a composite waveform (B—shows the sum of the fourwaves and indicates that this will control current as a function oftime) that is then converted into a current-time waveform by thecomputer-controlled current source. This current-time waveform etches aporosity-depth profile into the Si wafer (C—shows an etched siliconwafer with a porosity as a function of depth graph). Analogous to aFourier transform of the composite waveform, the resulting opticalreflectivity spectrum (D—an optical reflectivity spectrum showing energyas a function of frequency) displays the four frequency components ofthe original four sine waves as separate spectral peaks. The positionand intensity of each rugate spectral peak is influenced by thefrequency and amplitude, respectively, of its corresponding sinecomponent. Note that the overall spectral shape of the illuminatinglight source, as well as the bandwidth of the optical components andspectrometer used to measure the reflected or transmitted rugatespectra, also influence the measured reflectivity peak amplitudes.Further, note that increasing the frequency of a given sine componentnot only increases the energy (or peak position) of a correspondingreflectivity peak, but also results in an increased amplitude of eachpeak, absent any competing effects from the measuring system. Increasingthe amplitude of a given sine component results in an increasedamplitude of each spectral peak without affecting its energy (or peakposition), absent any competing effects from the measuring system. Witha rugate filter, the continuous variation of the refractive index of amaterial as a function of depth is used to create peaks of strongreflectivity at only specific wavelengths, and generally lowreflectivity away from these wavelengths. In the past, rugate filtershave been crudely created by depositing successive layers of materialsof different index of refraction onto a substrate. This method islimited by the ability to create extremely thin layers, by theavailability of suitable materials that can be deposited in theselayers, and by the stability of the resulting film against diffusion.Porous silica films overcome all of these limitations by allowing thecontinuous variation of the index of refraction in a film made of astable material with no separate components or deposited layers. Inaddition, the same etching process used to create pores, when employedunder certain conditions, is used to separate a film from its parentsilicon wafer.

In some embodiments, film creation and separation is realized byanodically etching p-type, boron-doped, (100)-oriented silicon with <1mΩ cm resistivity in a solution of 48% aqueous HF:ethanol (3:1 byvolume). A computer-generated waveform containing the encodinginformation is used to control the electrochemical reaction. The poroussilicon film is lifted off the crystalline silicon substrate using anelectropolishing reaction consisting of a 4 mA/cm anodic current appliedin a solution composition of 48% aqueous HF:ethanol (1:14.5 by volume)for 60 s. The resulting film, as thin as ten microns, is robust enoughto require no substrate. The combination of common processing techniquesand minimal material usage allows these films to be produced cheaply.Finally, the information in a rugate filter is encoded into the depth ofthe film, so the film can be divided into numerous small tags (tens ofmicrons in x-y dimensions), each of which is a type of rugate microtag,without any loss of information, further reducing cost.

Porous silica rugate microtags offer a range of advantages over existingproduct labeling or authentication solutions. The advantages offered bya silica microtag originate in a number of ways. Because an opticalspectrometer is required to observe the encoded signal, the barrier todecoding the signal, and even more so reproducing it, is much higherthan with a typical UPC (Universal Product Code) barcode. Layeredsecurity schemes utilizing silica microtags attached to, or embeddedwithin, an item to be authenticated, can include both information on theitems' packaging (e.g., text, 2D barcodes), and information stored inthe tag. The two pieces of information can be combined into a digitalsignature, such that a security violation would be noted if someonetampers with either the packaging or the item.

Since the microtags are encoded with information purely in their depth,rather than along their surface, they can be broken into pieces withfull depth, with each piece still containing all of the encodedinformation. This makes porous silica microtags suitable for forensicapplications, where the tag may be subjected to rough handling. As longas any full-depth piece of the tag can be recovered, the information isnot lost. So even after the use and disposal of a product, in all butextreme situations a rugate microtag is expected to survive. This is incontrast to RFID (Radio-Frequency Identification), which requiresinternal electrical connectivity, and UPC codes which require that thesurface of the label bearing the code remain intact.

The ability to make small tags is also an advantage. At sizes as smallas 20 microns across, the tags are inconspicuous enough to avoid casualinspection. This is helpful for both security and forensic applications.Tagging systems that rely on larger tags may expect a consumer to removethe tag upon purchase, but a tag that is small enough to avoid noticewill be less likely to be removed.

The microtag method and system (the “system”) encompasses the entiretyof the method for embedding information into a microtag, the method formeasuring the optical reflectivity of the microtag, the ‘channel code’,or method for mapping the 1's and 0's of binary data (‘information’)into controllable characteristics of the tag's spectral response, theapparatus required to make encoded films and tags and the method andapparatus to read encoded films and tags.

FIG. 3 is a block diagram illustrating an embodiment of basic systemconcepts from binary data input and encoding of a microtag to thereadout, decoding, and error correction of the information stored on amicrotag. In the example shown, a physical encoding process thatencompasses the electrochemistry and material science for controllingthe reflective spectral properties of porous silicon. The informationfor the tag is entered in to the write strategy system, which addssupplemental information (e.g., error correction code (ECC)). The writestrategy system also encodes all the information in a manner appropriatefor the physical encoding (e.g., an electrical current capable ofachieving encoding the desired information in pores by etching). Thewrite strategy is used to generate an encoded microtag which can then beread using a reader. The reader reads a reflectivity spectrum. Thereflectivity spectrum is decoded to extract the channel code which isthen checked and corrected for errors (e.g., ECC code and information isused to correct and check the data encoded in the microtag). In someembodiments, preprocessing, physical encoding, etching currentdetermination, microtag encoding, channel code encoding, errorcorrection code encoding are performed using a processor coupled to amemory where the memory is configured to provide the processor withinstructions. In some embodiments, reading the microtag, errorcorrection decoding, channel decoding, spectrum analysis are performedusing a processor coupled to a memory where the memory is configured toprovide the processor with instructions. In some embodiments, theprocessor executes software that instructs the processor for encodingand/or decoding of microtags.

Rugate filters, in contrast to Bragg filters, are known for lackingharmonics of the designed rugate peak frequency(ies). Reduction orelimination of harmonics simplifies decoding of reflectance spectra.However, rugate filters suffer from (i) sidelobes near each rugate peakdue to the finite spatial extent of the index variation function, and(ii) interference fringes across the entire spectrum due to poor indexmatching at interfaces and surfaces. These two effects (the rugateeffect including both peaks and sidelobes, and interference fringes)generally interfere, resulting in a more complex spectral structure.There are well-known techniques, such as index matching and apodization,that can be used to reduce the intensity of these effects(“rugate/fringe interference”), and indeed it is prevalent andcommonplace in the prior art of rugate filters that harmonics,sidelobes, or interference fringes are considered undesirable; mucheffort has gone into their reduction or elimination. The objective ofdecoding a rugate microtag is to retrieve as accurately as possible theinformation encoded into the microtag.

In some embodiments, sidelobes, interference fringes, and rugate/fringeinterference are turned to useful advantage, such as encodinginformation, by a thorough understanding of how these interferences arecreated, and how to predictably generate, control, and decode the totalspectral properties exhibited by optical films and tags, includingusing, rather than ignoring or suppressing, information encoded insidelobes, interference fringes, and their resultant interferences.

In some embodiments, each frequency of the current density waveform usedto etch a silicon wafer (“input waveform”) has a defined position(energy), amplitude, and phase. When a rugate microtag is interrogatedusing optical irradiation and an optical spectrometer, the reflectancespectrum comprises a multitude of peaks. “Optical spectrometer” meansherein a spectrometer operating in the visible band, including signalprocessing such as analog to digital converters in the output chain.Decoding reflectance spectra by suppressing or ignoring sidelobes,interference fringes, and their resultant interference, has had limitedsuccess in reconstructing the position (energy), amplitude, and phase ofthe input waveform; consequently, there has been limited success indecoding from the multipeak reflectance spectrum of a rugate microtagthe information encoded in the microtag (i.e., originally encoded in theinput waveform).

In some embodiments, information capacity of rugate microtags isincreased by including sidelobes, interference fringes, and theirresultant interferences in predictably encoding and decoding rugatemicrotags (i.e., to use the rugate “recovered phase” as an additionalform of useful information, either separately, or in combination withrugate peak amplitude and wavelength). The optical tags produced usingthe method herein are called “phase tags” to distinguish them from priorart optical tags. Phase tags can use phase, amplitude, and/or peakposition encoding and decoding, as explained below. The choice ofwhether encoding and decoding is done by phase, amplitude, and/or peakposition is driven by several factors, such as i) data capacity, ii)security, iii) ease of implementation, or iv) computational complexity(cost).

The ability to finely control the optical reflectivity spectrum enablesmany different possibilities for encoding data. The most obvious is abinary scheme, where numerous peaks of strong reflectivity are processedinto the optical reflectivity spectrum, and information is recovered bymeasuring the presence or absence of a peak at a set of predeterminedwavelengths. Up to 20 reflectivity peaks were shown achievable.

Control can also be exerted over the amplitude and width of areflectivity peak and peak spacings. Each additional spectral featurethat can be controlled offers a means to store more information. Forexample, in some embodiments 10 peaks are produced at 4 amplitudelevels, suggesting that 4¹⁰- or ˜1 million-spectral states might bepossible, which corresponds to ˜20 bits of information (2²⁰=˜1 million).Again, the control required to utilize those 10 peaks to actually encodeand decode 20 bits of information was not demonstrated.

Below are some examples of 4″ heavily-doped silicon wafers using theprior art techniques described above. These examples demonstrate some ofthe variations and limitations encountered in attempting to implementthe prior art encoding methods described above.

FIG. 4 are graphs illustrating a single and a composite reflectancespectrum read from an embodiment of microtags without any normalization.In the example shown, the upper graph shows the positions of 8 opticallyread peaks based on the pore density in a microtag. The lower graphshows a composite of each of the 8 peaks read back from a set of tagsfrom 9 identically made films from multiple wafers. As can be seen fromthe lower graph, variations in peak energy (position) are such that onecannot immediately discern peak position when tags are produced inquantity utilizing the majority of a single, 4″ wafer surface.

FIG. 5A are graphs illustrating embodiments of normalized peak energies.In the example shown, the peaks in the upper plot are normalized byusing the lowest and highest energy peaks as references and rescalingthe peak energy. The relative peak energy is actually well maintained.This allows information to be encoded in peak position despite theobserved manufacturing process variations in peak position. The toppanel shows the same data that is plotted in the bottom panel of FIG. 4,but with the energy of each point rescaled using the lowest and highestenergy peaks in each spectrum as reference markers. The rescaled energyscale measures the position of every peak in each spectrum as a fractionof the energy difference between the two reference peak positions. Thelower plot of FIG. 5A uses a similar technique (using the amplitude at agiven position and rescaling each data point as a fraction of thatamplitude) shows that variations in peak amplitude cannot be as handilyremoved as for the case of variations in peak position. A comparison ofthe amplitude range of the fourth position and the amplitude range atthe seventh position illustrates overall range variation; moreover, theamplitudes do not resolve in discrete clusters of amplitudes at anygiven position. All measured peaks in this plot were encoded using thesame amplitude, so discrete clusters in the y-axis are not expected. Thelesson from this plot is that variation in measured peak amplitude isnot reduced across the spectrum by normalizing the peak amplitudes.Amplitude that cannot be assigned with confidence to a known position,or an amplitude at a given position that cannot be determined withconfidence cannot be used to decode a rugate microtag. In the exampleshown, the process variations in the etching of a wafer mean that thevalues associated with amplitude and some positions in the coding anddecoding of rugate particles are potentially lost, which degrades theinformation capacity of rugate microtags.

The dominant cause of tag manufacturing process variation is in theetching rate. Rugate peaks are altered by etching rate variation inpredictable way. Referring to Eqn. (3) below, we can extract thefrequency of a rugate peak (f_(r)) as a function of etching rate.

$f_{r} = {\frac{2\; n_{0}}{\lambda} = {2\;{n_{0} \cdot \frac{f_{t}}{v_{e}}}}}$

In Equations (1) and (2), n₀ is the average index of refraction of thefilm, f_(t) is the temporal frequency of the etching current, and v_(e)is the etching rate. We can consider a change in the etching rate by asmall fraction γ of the original v_(e). Equation (1) above then becomes

$\begin{matrix}{f_{r} = {{2\;{n_{0} \cdot \frac{f_{t}}{v_{e} \cdot \left( {1 + \gamma} \right)}}} = {{2\;{n_{0} \cdot \frac{f_{t}}{v_{e}} \cdot \left( {1 - \gamma + {O\left( \gamma^{2} \right)}} \right)}} = {f_{r} \cdot \left( {1 - \gamma + {O\left( \gamma^{2} \right)}} \right)}}}} & {{Eqn}.\mspace{14mu} 2}\end{matrix}$

For small changes in the etching rate (γ<<1), the rugate peak positionschange in a way which can, to a good approximation, be removed withlinear rescaling in energy (or frequency) (e.g., see top of FIG. 5A).

The above energy rescaling method requires that the reference peaksappear in the same place in every spectrum. As such, the reference peakscannot hold any information. To avoid using two peaks for scaling andnot for information storage, an alternate method of storing informationis used that inherently includes partial scaling information within eachspectrum. The method requires restricting peak positions to a discretenumber of possible energies. For example, in the spectrum shown in thetop panel of FIG. 4, the rugate peaks are encoded (i.e., the etchingwaveform is generated and applied to the wafer bath) using etchingcurrent frequencies that correspond to seven times a base frequency stepbetween each rugate peak. Thus, each step delineates an allowed rugatepeak position, providing 49 possible rugate peak positions. The rugatepeak at the lowest scaled energy is then used as the single referencepeak. Then next step is to try to determine empirically (“guess”) thenumber of allowed rugate peak positions that lie between the referencepeak and the rugate peak with the highest scaled energy.

FIG. 5B is a flow diagram illustrating an embodiment of a process forencoding energy peaks of an identifier. In the example shown, in 500 areadable spectral range is defined. In 502, the spectral range isdivided into N bins. In 504, a reference peak is encoded in center of abin near one end of the spectral range. In 506, data pattern peaks areencoded in the center of bins within the spectral range.

FIG. 5C is a flow diagram illustrating an embodiment of a process fordecoding energy peaks of an identifier. In the example shown, in 510 areference peak position is received. In 512, data pattern peakspositions are received. In 514, a farthest peak of the data peaks fromthe reference peak is determined. In 516, determine data peak bins byfinding lowest error for all potential positions of farthest peak fromreference peak.

In some embodiments, within an allowed envelope of where peaks arepossible, a number of bins for peaks are determined (e.g., 65 bins, 50bins, etc.). A readable spectral range is defined, such that no matterhow the peaks shift during manufacturing they are still within thespectral range of the reader. That range is divided into N bins, any ofwhich can contain a peak. A reference peak is encoded near one end ofthe spectral range—for example, bin 1. The rest of the peaks in a datapattern are encoded (e.g., etched) to each lie at the center of a bin.In some embodiments, there is a maximum allowable distance between peaksto ensure that there are enough peaks to give a good triggering signalfor when the reader is searching for tags. The reader then finds thereference peak (e.g., the peak in bin 1) and any other peaks in therange of the reader including the peak the farthest from the referencepeak. The bin number of the peak farthest from the reference peak isfound by assuming a bin number ranging from bin N to the reference bin.For each of these assumed bin numbers, the bin centers are calculatedfor the whole readable range and each peak assigned to its closest bincenter. Then the squared deviation of each peak from its bin center isadded together for all peaks in each case, and the highest bin numberwith the smallest total squared deviation is chosen as most likely. Thenall the peak positions are known in terms of scaled energy. FIG. 6 aregraphs illustrating an embodiment of allowed rugate peak positions. Inthe example shown, the allowed rugate peak positions (bars) are plottedwith the measured peak positions displayed in FIG. 5A (circles) for 3different guesses for the actual position of the highest scaled energyrugate peak. The bottom panel is a zoomed-in look at the middle sectionof the top panel shows all 49 possible rugate peak positions, with 3different guesses (applied to the data from FIG. 5A) for the number ofallowed rugate peak positions. In the bottom panel, a closer look at theeffect of different guesses at the correspondence between allowed peakpositions and measured positions is displayed for a peak near the centerof the spectral range. It is clear that the correct guess (49 spaces)provides the only reasonable fit.

FIG. 7 is a graph illustrating the squared error in measured peakposition summed for each peak in a spectrum in one embodiment. In theexample shown, the squared error in the measured peak position isplotted as a function of different guesses for the actual position ofthe highest scaled energy peak used as a second reference. Each spectrumfrom FIG. 6 is plotted. The empirical accuracy (“goodness”) of eachguess is quantified by summing the squared difference of each peakposition from the calculated allowed positions for each guess. Then theguess with the lowest squared difference can be taken as the best choiceand used for decoding.

With the one reference peak scaling described above, information isencoded using variation in peak position and number. The informationcapacity is determined by the number of allowed peak positions, thesmallest achievable distance between two peaks, and to a lesser extentthe largest achievable distance between two peaks.

Both (i) rescaling position data obtained from reflectance spectra, and(ii) restricting peak positions to a discrete number of possibleenergies during encoding and fitting data obtained from reflectancespectra to the known number of energies, degrade the potentialinformation capacity of rugate microtags. Accordingly there is demandfor an improved method of decoding rugate microtags that provides asubstantial improvement in information capacity, especially a method ofincluding rugate phase information, i.e., values of phase φ_(i) (asexplained below), in predictably encoding and decoding rugate microtags.The system solves the technical problem of including rugate phaseinformation in predictably encoding and decoding rugate microtags,thereby substantially increasing the information capacity of rugatemicrotags.

The system decodes rugate microtags by calculating values of rugatephase φ_(i) or reliable proxies of rugate phase φ_(i) (individually andcollectively, “rugate phase information”). The use of rugate phaseinformation does not detract from the information storage mechanisms ofthe existing art, but adds a new way to store information that can beused to add to the total information capacity of a rugate microtag.

The term n(z) is the refractive index variation n of a simple one-peakrugate filter at a function of depth z in an etched film or tag.

$\begin{matrix}{{n(z)} = {n_{0} + {\frac{n_{a}}{2}{\sin\left( {\frac{4\pi\; n_{0}z}{\lambda_{i}} + \phi_{i}} \right)}}}} & {{Eqn}.\mspace{20mu} 3}\end{matrix}$

This can be easily extended to “multiple peak” rugate filters by addingadditional sine terms of appropriate frequency and phase. Here λ_(i) isthe wavelength of the rugate peak, n₀ is the average refractive index,n_(a) is the peak-to-peak refractive index variation, and φ_(i) is therugate phase.

The reflectivity of the rugate filter, r_(rug), can be adapted as:

$\begin{matrix}{{r_{rug} = \frac{\frac{{- \varrho}\;\omega}{4}\sinh\left\{ {T \cdot \left\lbrack {\left( \frac{\varrho\omega}{4} \right)^{2} - \left( {\omega - \omega_{i}} \right)^{2}} \right\rbrack^{\frac{1}{2}}} \right\} e^{{\mathbb{i}\phi}_{i}}}{\begin{matrix}{{{\left\lbrack {\left( \frac{\varrho\;\omega}{4} \right)^{2} - \left( {\omega - \omega_{i}} \right)^{2}} \right\rbrack^{\frac{1}{2}} \cdot \cosh}\left\{ {T \cdot \left\lbrack {\left( \frac{\varrho\omega}{4} \right)^{4} - \left( {\omega - \omega_{i}} \right)^{2}} \right\rbrack^{\frac{1}{2}}} \right\}} +} \\{{{\mathbb{i}} \cdot \left( {\omega - \omega_{i}} \right) \cdot \sinh}\left\{ {T \cdot \left\lbrack {\left( \frac{\varrho\omega}{4} \right)^{2} - \left( {\omega - \omega_{i}} \right)^{2}} \right\rbrack^{\frac{1}{2}}} \right\}}\end{matrix}}}\mspace{79mu}{where}} & {{Eqn}.\mspace{14mu} 4} \\{\mspace{79mu}{{\omega_{i} = \frac{2\;\pi}{\lambda_{i}}},{\omega = \frac{2\;\pi}{\lambda}},{T = {n_{0^{-}}L}},{{{and}\mspace{14mu}\varrho} = \frac{n_{a}}{n_{0}}}}} & {{Eqn}.\mspace{14mu} 5}\end{matrix}$ω in Equation 4 is the optical frequency; T is the optical thickness; Lis the physical thickness of a given filter, film, or tag; and Q is theratio of the peak-to-peak index variation to the average index.

The above expression r_(rug) includes the rugate peak and its sidelobes,but not the effects of filter surfaces and interfaces. The additionalreflectivity in the pure rugate case is solely from the surfaces of thefilter. Equation 6 below is for the reflectivity, r_(s), caused by theinterference of internal reflections from the surfaces of a filterimmersed in air (the simplest case for discussion purposes), but it isstraightforward to extend Equation 4 to include buried interfaces ordifferent immersed media. This discussion will continue the analysis ofthe simple case of a rugate filter immersed in air.

$\begin{matrix}{r_{s} = \frac{\left( \frac{1 - n_{0}}{1 + n_{0}} \right)\left( {1 - {\mathbb{e}}^{{- 2}{\mathbb{i}\omega}\; T}} \right)}{1 - {\left( \frac{1 - n_{0}}{1 + n_{0}} \right)^{2}{\mathbb{e}}^{{- 2}{\mathbb{i}}\;\omega\; T}}}} & {{Eqn}.\mspace{14mu} 6}\end{matrix}$

The total reflectance of a rugate filter with surfaces, R, is measurableusing a white light and optical spectrometer, is the square of the totalreflectivity,R=(r _(rug) +r _(s))·(r _(rug) +r _(s))*=|r _(rug)|² +|r _(s)|² +r_(rug) *·r _(s) +r _(rug) ·r _(s)*  Eqn. 7

Where * refers to the complex conjugate. Equation 7 above contains 4terms, two of which (r_(rug)·r_(s)*+r_(rug)*·r_(s)) are the so-calledcross terms. The cross terms contain all of the interference betweenr_(rug) and r_(s). FIG. 8 shows the magnitude squared of both r_(rug)and r_(s) for typical conditions and one encoded rugate peak. While|r_(s)| oscillates with a consistent amplitude across all energies,|r_(rug)| is sharply peaked at the encoded rugate energy and falls tonearly zero quickly away from the encoded rugate energy. From this wecan conclude that the cross terms, which contain r_(rug), are alsolargest near the encoded rugate energies, and become very small quicklyaway from the encoded rugate energies. By fitting a measured reflectancespectrum at frequencies far from the rugate peak to the function|r_(s)|², one can obtain fitted values for n₀ and the optical thicknessT. Using these measured values, it is possible to then fit the portionof the reflectance spectrum near the rugate peak to the entire Rfunction above, with only λ_(i), φ_(i), and Q as unknowns in Equation 7.These fit parameters are close enough to orthogonal to allow a decisivefit.

FIG. 8 is a graph illustrating the squared magnitude of both thesurface-derived interference fringes r_(s) and a typical rugate peakr_(rug) in one embodiment. In the example shown, while |r_(s)|² hasequal intensity maxima across the range of energies, |r_(rug)|² containsappreciable intensity only near the rugate peak. To apply the abovemethod, the variability in the etching rate must be accounted for duringmicrotag manufacture. The interference effect depends on the relativeposition in frequency (or energy) of a rugate peak and thesurface-derived interference fringes. As shown in FIG. 8, thesurface-derived reflectivity is periodic in energy, comprising ofrepeating identical maxima and minima. The position of each maximum infrequency, f_(m), is

$\begin{matrix}{f_{m} = {\frac{{2m} + 1}{4\;{n_{0} \cdot t \cdot v_{e}}}\left( {{m = 0},1,2,3,\;\ldots}\mspace{14mu} \right)}} & {{Eqn}.\mspace{14mu} 8}\end{matrix}$where n₀ is the average index of refraction of the film, t is the totaletching time, and v_(e) is the etching rate. The 1/v_(e) dependence isthe same dependence on etching rate as the rugate peak position. Thuschanges in etching rate preserve the relative position of rugate peaksand surface-derived interference fringes, and the interference effectsdo not depend strongly on etching rate.

The ability to effectively extract the fundamental peak position λ_(i),peak amplitude (related to Q), and rugate phase φ_(i) from a rugatefilter reflectance spectrum offers a significant advantage forinformation storage. In some embodiments, a rugate tag system relies ondesigning and measuring changes in the reflectance peak positions andamplitudes to store information. This means at least one reference peakmust be created in the encoding of tags in order to judge relative peakamplitudes or the relative position of other peaks. However, as shown inFIGS. 4 and 9, both the apparent peak amplitude and its position inwavelength depend on the rugate phase. This behavior is due tointerference between r_(rug) and r_(s). These interference effects, andassociated uncertainties in decoding, substantially limit theinformation capacity of an industrial application of prior art methods.In reality, peak amplitude and peak shape (and therefore “apparent peakposition”) depend on rugate phase, which in turns depends uponinterference between r_(rug) and r_(s). Thus, in prior art methods,which interrogate rugate peaks generically and assume, inter alia,Gaussian or pure sinc-like form, not only is the interference treated asnoise, which reduces the information capacity of the tags, but “apparentpeak positions” (arising from asymmetric shapes) in the decoded outputdoes not accurately reflect the encoded peak positions in the etchingwaveform.

By encoding, interrogating, and decoding rugate microtags with phase inmind, the system achieves an increase in the information capacity of themicrotag by using phase as all or part of a signal rather thanconsidering it noise.

In some embodiments, information is encoded using the phase φ_(i) of arugate peak in the following way. A phase value φ_(i) is chosen for therugate peak of interest. While φ_(i) can take on any value, values ofφ_(i) greater than 2π or less than zero result in repetition of spectracreated using values from zero to 2π. It may be convenient to use valuesof φ_(i) that lie in any 2π range independent of absolute values ofφ_(i). φ_(i) is physically encoded by electrochemically etching andcreating a nanoporous filter using the rugate index of refractionvariation n(z) as shown in Eqn. 1, using the chosen value of rugatephase φ_(i).

FIG. 9 is a graph illustrating an embodiment of a calculated rugatefilter reflectance spectrum. In the example shown, the variation of arugate filter reflectance spectrum obtained by altering asingle-frequency etching waveform by phase alone (constant frequency andamplitude) in a twenty degree increments. In each case only one peak isencoded, at constant wavelength and amplitude. Each spectrum correspondsto a different rugate phase.

To decode the phase, the reflectance spectrum is measured and the resultcompared to the functional form of R (Eqn. 7), preferably by a fittingalgorithm. The fitting algorithm may utilize a number of constants asconvenient to solve for the parameters of interest. It is not requiredto solve Equations 4 to 6 in their entirety of detail; it may beadequate to approximate some portions of the equations. For example, inequation 6, in both the numerator and denominator n₀ appears in the sameform, which we can define as δ:

$\delta = \frac{n_{0} - 1}{n_{0} + 1}$

In the rugate microtags, the average refractive index n₀ is about 1.2,so δ is on the order of 0.1.

FIG. 10 is a graph illustrating an embodiment of a comparison of fullsurface-derived reflectance to a simple approximation. In the exampleshown, the solid line shows Equation 6 evaluated with δ=0.1 and T=40 um.The dashed line shows the effect of ignoring the exponential term in thedenominator. The lines are close to the same, with the maximumdifference at the top of the peak near 565 nm enlarged in the inset.Referring to equation 6, the exponential terms are of order 1, so theexponential term of the denominator is of order 0.01, and can be ignoredto produce a very close approximation from a simpler equation. As longas the important functional characteristics of Equations 4 to 7 aremaintained, it is up to the user to determine the level of granularitythat is useful.

In any case, since the rugate phase φ_(i) is a parameter of R viaEquation 4, once the fitting is complete, the original phase φ_(i) isobtained. This method is possible for any or all of the desiredparameters used in both the index of refraction variation n(z) (Equation3) and the functional form of R (Equation 7). The fitting is donecomputationally using only the reflectance spectrum, and without need ofa reference peak.

FIG. 11 are graphs illustrating embodiments of four different etchingwaveforms of the same frequency and amplitude, but different phases. Inthe example shown, each phase could correspond to a different piece ofdata. As an example of data storage and retrieval using the methoddescribed above, four different microtags are encoded using etchingcurrent density waveforms, all composed of the same single frequency andthe same amplitude, but differing in initial rugate phase φ_(i). Oncemanufactured, the reflectance of each microtag is measured.

FIG. 12 are graphs illustrating an embodiment of simulated reflectancespectra corresponding to the four current density waveforms along withfitted spectra. In some embodiments, the four current density waveformscorrespond to those shown in FIG. 11 (dotted lines) and the fittedspectra are obtained using Eqn. 7 (solid lines). In the example shown, asimulated spectrum for each of the four current density waveforms isshown. Equation 7 is fitted to each spectrum by using an algorithm suchas non-linear least squares. The output of the fit is a value anduncertainty for each parameter in the fit equation, including rugatephase φ_(i). Examples of equation 7 calculated for each simulatedspectrum are also shown. Depending on the quality of the spectrometerand signal processing used for data capture, this method enables one toaccurately store and read many more different phases than the four usedin this example.

FIG. 9 shows that the rugate phase controls a number of spectralproperties, notably the rugate sidelobe asymmetry and the peak width.Elimination of fitting the function R may be useful to reducecomputational complexity (hence cost) of the overall systemimplementation.

FIG. 13 is a graph illustrating an embodiment of a relation betweensidelobe asymmetry and rugate phase. In the example shown, by measuringthe ratio of sidelobe amplitudes in each spectrum shown in FIG. 4, aclear indication of rugate phase can be extracted. This is the simplestof numerous techniques that may be used to determine rugate phase from areflectance spectrum. Of many potential spectral properties that couldbe used to eliminate fitting the function R and associated computation,yet be able to accurately infer controllable index function variables,the sidelobe asymmetry is particularly convenient to measure, since itrequires no reference information. Although the spectral effect of achange in rugate phase clearly exists over a range of wavelengths nearthe rugate peak, phase information can be extracted using as few as twodata points, as shown in FIG. 13; the two data points can then be usedto compute a proxy for rugate phase φ_(i), in this case sidelobeasymmetry.

FIG. 14 is a graph illustrating an embodiment two rugate index profiles.In the example shown, two rugate index profiles are shown that weregenerated in MatLab using values n_(o)=1.125, n_(a)=0.004, λ=674.2 nm,φ₁=180 deg, and φ₂=270 deg for values of z ranging from 0 to 2 μm. Thegraph illustrates two different sine-wave index profiles, differing onlyby phase (180 degrees and 270 degrees respectively); i.e., FIG. 14compares the sine-wave index profiles of (i) a first rugate microtagproduced with an etching current density waveform consisting of a singlesine wave of frequency X and (ii) a second rugate microtag produced withan etching current density waveform consisting of a single sine wave ofthe same frequency X, but with a 90 degree delay in phase.

FIG. 15 is a graph illustrating an embodiment of side lobe asymmetrycalculation for two rugate peaks differing only by phase. In the exampleshown, spectra were calculated using standard optical transfer matrixmethods applied to interference of multiple “layers”. Note that in thecase of rugate filters, physical “layers” are not discrete, rather theyare smoothly and continuously varying. Inputs to the matrix were the tworugate index profiles shown in FIG. 14 for a tag thickness L of 15 μm.FIG. 15 shows the resultant rugate peaks that would be produced by eachindex profile to illustrate computation of sidelobe asymmetry. Thismethod of extracting phase information is called the “sidelobe asymmetrymethod” and is explained in the next paragraph.

Sidelobe asymmetry is the quotient obtained by dividing the peakreflectance of the first sidelobe below a major reflectance peak of arugate microtag by the peak reflectance of the first sidelobe above amajor reflectance peak, shown in FIG. 15. The quotient varies smoothlyover a range of values of the encoded rugate phase φ_(i). As such, thesidelobe asymmetry can be encoded into a rugate peak, and used to storeinformation. Sidelobe asymmetry can be easily computed from thereflectance spectrum of a rugate microtag without the need for curvefitting, as described in the preceding paragraph. In addition, sidelobeasymmetry can be encoded by adjusting the rugate peak position whilemaintaining a fixed microtag optical thickness. This method is generallyless preferred however, because it may interfere with direct peakposition encoding.

The example illustrated FIGS. 14 and 15 requires precise knowledge ofthe relative position in wavelength between the rugate peak and thenearby surface-derived interference fringes, the quality of which isprimarily dependent upon the quality of the spectrometer and signalprocessing used during interrogation and readout of a rugate particle.Depending on the nature of the manufacturing variability of the rugatefilters, either simplified methods (such as using sidelobe asymmetrymethod described above) or more computationally intensive fittingmethods can be used to extract φ_(i) or other basic parameters from themeasured reflectance spectra of rugate filters. Additional examples offitting methods include any form of non-linear regression analysis, suchas the non-linear least squares method.

Phase encoding of information can utilize the number of different phasevalues φ_(i) determinable after consideration of manufacturing andreflectance measurement variations, as well as consideration of systemdecoding tolerances and error correction (ECC).

There exist various methods of mapping information bits (b) intophysical media (known as “channel coding”) that are well known ininformation theory and in such industries as the telecommunications,hard disk drive, flash memory, and optical data storage industries(e.g., algebraic codes for data transmission). Using the simple relation2^(b)=p that relates the number of values p required to provide b binarydigits (“bits”), 4 distinct values of φ_(i) could provide 2 bits of rawinformation capacity, 8 values of φ_(i) could provide 3 bits of rawinformation capacity, and so on. Channel codes and ECC extract anoverhead to provide for additional robustness and efficiency during themeasurement and decoding process, such that information bits availableto the end user should be distinguished from raw (or maximumtheoretical) capacity available, as is well known in the field.Extraction of phase information, and associated encoded data, can bedone for every determinable rugate peak in the reflectance spectrum of atag to further increase information capacity. There are many ways toutilize phase, amplitude, and peak position to further increaseinformation capacity, such as are used in typical digital communicationsystems.

There also exist many approaches to encoding that do not rely on precisedetermination of φ_(i) or other parameters, such as partial responsemaximum likelihood (PRML) codes and other methods that can deal withoverlapping distributions of the various parameters. It will be obviousto those skilled in the art as to how to choose the appropriate channelcodes and/or error correction code once the total system signal-to-noiseratio has been characterized, along with a thorough understanding of thephysical variations encountered, including random and systematic noisesources.

The use of multiple frequencies, and the associated sidelobes,interference fringes, and their resultant interferences, means thephase-decoding aspects of the system are applicable to decoding allrugate microtags.

In some embodiments, the encoded information can be useful for means oflabeling or authenticating various products or objects when the films,or pieces thereof, are attached to, or embedded within a product,object, or other item. In various embodiments, the encoded informationis used to label or authenticate one or more of the following: a powder,a pill, a liquid drug, an art piece, a chip, a consumer device, anelectronic device, or any other appropriate object that it is desired tolabel or authenticate. In some embodiments, information encoded in amicrotag is used to determine whether or not an item is as desired. Forexample, an object is labeled using a microtag; the tag is read and theread tag is compared to a known tag signature associated with theobject.

Applications for which phase tags (e.g., the rugate microtags) offer animproved method of encoding and decoding information, either using phasesolely, or in combination with peak amplitude and/or position(wavelength) encoding, include: labeling, tracking, and/orauthentication. In summary, a method and system of encoding,manufacturing, and decoding a rugate microtag, comprises:

determining a collection of waveform traits comprising phase values andoptionally comprising traits selected from the group comprisingfrequency values and amplitude values;

coding information using the collection of traits;

assembling an acid-etching apparatus in which to acid-etch a siliconwafer using an etching current waveform;

mounting a silicon wafer in the apparatus;

generating an etching current waveform that contains the codedinformation:

acid-etching a silicon wafer using the waveform to create region ofporous silicon in the silicon wafer;

lifting a film of porous silicon from the wafer using anelectropolishing reaction;

breaking or cutting porous silicon film into rugate microtags;

oxidizing the porous silicon film to create a porous silica film;

applying rugate microtags to objects or embedding rugate microtags inobjects;

measuring the reflectance spectrum of a rugate microtag associated withan object using an optical spectrometer;

detecting in the reflectance spectrum the peak reflectance of eachrugate peak and of the sidelobes nearest each rugate peak in wavelength;

dividing the peak reflectance of the first sidelobe below a given rugatepeak by the peak reflectance of the first sidelobe above the rugate peakto obtain a quotient;

converting the quotient to rugate phase;

repeating the preceding two steps for each rugate peak in thereflectance spectrum of the rugate microtag,

thereby determining the rugate phase of each rugate peak the etchingcurrent waveform used in the production of the rugate microtag;

if frequency traits were used to code the information, determining foreach rugate peak in the reflectance spectrum the corresponding frequencyused in the production of the rugate microtag;

if amplitude traits were used to code the information, determining foreach rugate peak in the reflectance spectrum the peak amplitude used inthe production of the rugate microtag;

determining the information coded in the rugate microtag based on therugate phase values, and optionally based on values selected from thegroup comprising frequency values and amplitude values, recovered fromthe reflectance spectrum of the rugate microtag.

In some embodiments, the method and system storing information in theoptical reflectance of the rugate microtag comprises:

producing a rugate microtag reflectance spectrum, either byelectrochemical etching and measurement using an optical spectrometer orby calculation;

dividing the peak reflectance of the first sidelobe below a given rugatepeak by the peak reflectance of the first sidelobe above the rugate peakto obtain a quotient;

repeating the preceding two steps using different values of the rugatephase until the quotient is a desired value;

assigning the final value of the quotient to a piece of information tobe stored;

repeating the preceding four steps for each rugate peak in thereflectance spectrum of the rugate microtag,

manufacturing rugate microtags with the desired sidelobe asymmetrycorresponding to the information to be stored;

measuring the reflectance spectrum of a rugate microtag using an opticalspectrometer;

detecting in the reflectance spectrum the peak reflectance of eachrugate peak and of the sidelobes nearest each rugate peak in wavelength;

recalculating the quotient described in step two;

thereby determining the piece of information stored in the rugatemicrotag reflectance spectrum.

In some embodiments, the method of calculating the rugate phase of eachsinusoidal component of an etching current waveform used in theproduction of a rugate microtag from analysis of the optical reflectanceof the rugate microtag comprises:

measuring the reflectance spectrum of a rugate microtag using an opticalspectrometer;

fitting the measured reflectance spectrum of each rugate peak toequation 4 using regression analysis;

solving equation 4 for the rugate phase of the rugate peak;

repeating the preceding two steps for each rugate peak in thereflectance spectrum of the rugate microtag,

thereby determining the rugate phase of each sinusoidal component of theetching current waveform used in the production of the rugate microtag.

In some embodiments, the method of calculating the peak wavelength ofeach rugate component of an etching current waveform used in theproduction of a rugate microtag from analysis of the optical reflectanceof the rugate microtag comprises:

measuring the reflectance spectrum of a rugate microtag using an opticalspectrometer;

fitting the measured reflectance spectrum of each rugate peak toequation 4 using regression analysis;

solving equation 4 for the wavelength of each rugate peak;

repeating the preceding two steps for each rugate peak in thereflectance spectrum of the rugate microtag,

thereby determining the peak wavelength of each rugate component of theetching current waveform used in the production of the rugate microtag.

In some embodiments, a reflectance spectrum is measured from a rugatemicrotag, and the amplitude, frequency (and/or scaled energy), andrugate phase of each sinusoidal component of the etching current aredetermined based on the measured rugate peaks. In some embodiments, themethod of calculating the peak amplitude components of an etchingcurrent waveform used in the production of a rugate microtag fromanalysis of the optical reflectance of the rugate microtag comprises:

measuring the reflectance spectrum of a rugate microtag using an opticalspectrometer;

fitting the measured reflectance spectrum of each rugate peak toequation 4 using regression analysis;

solving equation 4 for the amplitude of each rugate peak;

repeating the preceding two steps for each rugate peak in thereflectance spectrum of the rugate microtag,

thereby determining the peak amplitude components of the etching currentwaveform used in the production of the rugate microtag.

In some embodiments, the method of decoding a rugate microtag, whereinthe collection of traits for components of an etching current waveformused in the production of a rugate microtag are decoded using one of thepreceding methods.

Although the foregoing embodiments have been described in some detailfor purposes of clarity of understanding, the invention is not limitedto the details provided. There are many alternative ways of implementingthe invention. The disclosed embodiments are illustrative and notrestrictive.

What is claimed is:
 1. A system for decoding energy peaks of anidentifier, comprising: A decoder configured to: receive a referencepeak position associated with an identifier, wherein the identifiercomprises a rugate microtag; receive a set of data pattern peakpositions associated with the identifier; determine a farthest peak ofthe set of data pattern peak positions from the reference peak position;and determine a set of data pattern peak bins from the set of datapattern peak positions, wherein the set of data pattern peak bins arebased at least in part on a lowest error for a set of potential datapattern peak bins corresponding to the set of data pattern peakpositions for a potential bin position for the farthest peak.
 2. Asystem as in claim 1, wherein the identifier has an identifying datavalue determined based at least in part on the data pattern.
 3. A systemas in claim 2, wherein the identifying data value includes an errorcorrection code data.
 4. A system as in claim 2, wherein the identifyingdata value comprises a digital signature value.
 5. A system as in claim2, wherein the identifying data value includes a channel code data.
 6. Asystem as in claim 1, wherein the identifier is added to an object foridentification.
 7. A system as in claim 1, wherein the rugate microtagcomprises oxidized etched silicon.
 8. A system as in claim 1, whereinthe identifier identifies an object by being optically read.
 9. A systemas in claim 8, wherein optically reading comprises detecting areflectance spectrum.
 10. A system as in claim 9, wherein opticallyreading comprises optically reading using one or more of the following:reading using visible wavelengths, reading using infrared wavelengths,or reading using ultraviolet wavelengths.
 11. A method for decodingenergy peaks of an identifier, comprising: receiving a reference peakposition associated with an identifier, wherein the identifier comprisesa rugate microtag; receiving a set of data pattern peak positionsassociated with the identifier; determining, using a processor, afarthest peak of the set of data pattern peak positions from thereference peak position; and determining a set of data pattern peak binsfrom the set of data pattern peak positions, wherein the set of datapattern peak bins are based at least in part on a lowest error for a setof potential data pattern peak bins corresponding to the set of datapattern peak positions for a potential bin position for the farthestpeak.
 12. A method as in claim 11, wherein the identifier has anidentifying data value determined based at least in part on the datapattern.
 13. A method as in claim 12, wherein the identifying data valueincludes an error correction code data.
 14. A method as in claim 12,wherein the identifying data value comprises a digital signature value.15. A method as in claim 12, wherein the identifying data value includesa channel code data.
 16. A method as in claim 11, wherein the identifieris added to an object for identification.
 17. A method as in claim 11,wherein the rugate microtag comprises oxidized etched silicon.
 18. Amethod as in claim 11, wherein the identifier identifies an object bybeing optically read.
 19. A method as in claim 18, wherein opticallyreading comprises detecting a reflectance spectrum.
 20. A method as inclaim 19, wherein optically reading comprises optically reading usingone or more of the following: reading using visible wavelengths, readingusing infrared wavelengths, or reading using ultraviolet wavelengths.